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Non-response is common in longitudinal surveys, reducing efficiency and introducing the potential for bias. Principled methods, such as multiple imputation, are generally required to obtain unbiased estimates in surveys subject to missingness which is not completely at random. The inclusion of predictors of non-response in such methods, for example as auxiliary variables in multiple imputation, can help improve the plausibility of the missing at random assumption underlying these methods and hence reduce bias. We present a systematic data-driven approach used to identify predictors of non-response at Wave 8 (age 25-26) of Next Steps, a UK national cohort study that follows a sample of 15,770 young people from age 13-14 years. The identified predictors of non-response were across a number of broad categories, including personal characteristics, schooling and behaviour in school, activities and behaviour outside of school, mental health and well-being, socio-economic status, and practicalities around contact and survey completion. We found that including these predictors of non-response as auxiliary variables in multiple imputation analyses allowed us to restore sample representativeness in several different settings, though we acknowledge that this is unlikely to universally be the case. We propose that these variables are considered for inclusion in future analyses using principled methods to explore and attempt to reduce bias due to non-response in Next Steps. Our data-driven approach to this issue could also be used as a model for investigations in other longitudinal studies. [ABSTRACT FROM AUTHOR]

Background: Research suggests that there have been inequalities in the impact of the coronavirus disease 2019 (COVID-19) pandemic and related non-pharmaceutical interventions on population mental health. We explored generational, sex, and socioeconomic inequalities during the first year of the pandemic using nationally representative cohorts from the UK. Methods: We analysed data from 26772 participants from five longitudinal cohorts representing generations born between 1946 and 2000, collected in May 2020, September–October 2020, and February–March 2021 across all five cohorts. We used a multilevel growth curve modelling approach to investigate generational, sex, and socioeconomic differences in levels of anxiety and depressive symptomatology, loneliness, and life satisfaction (LS) over time. Results: Younger generations had worse levels of mental and social wellbeing throughout the first year of the pandemic. Whereas these generational inequalities narrowed between the first and last observation periods for LS [−0.33 (95% CI −0.51 to −0.15)], they became larger for anxiety [0.22 (0.10, 0.33)]. Generational inequalities in depression and loneliness did not change between the first and last observation periods, but initial depression levels of the youngest cohort were worse than expected if the generational inequalities had not accelerated. Women and those experiencing financial difficulties had worse initial mental and social wellbeing levels than men and those financially living comfortably, respectively, and these gaps did not substantially differ between the first and last observation periods. Conclusions: By March 2021, mental and social wellbeing inequalities persisted in the UK adult population. Pre-existing generational inequalities may have been exacerbated with the pandemic onset. Policies aimed at protecting vulnerable groups are needed. [ABSTRACT FROM AUTHOR]

Multiple studies across global populations have established the primary symptoms characterising Coronavirus Disease 2019 (COVID-19) and long COVID. However, as symptoms may also occur in the absence of COVID-19, a lack of appropriate controls has often meant that specificity of symptoms to acute COVID-19 or long COVID, and the extent and length of time for which they are elevated after COVID-19, could not be examined. We analysed individual symptom prevalences and characterised patterns of COVID-19 and long COVID symptoms across nine UK longitudinal studies, totalling over 42,000 participants. Conducting latent class analyses separately in three groups ('no COVID-19', 'COVID-19 in last 12 weeks', 'COVID-19 > 12 weeks ago'), the data did not support the presence of more than two distinct symptom patterns, representing high and low symptom burden, in each group. Comparing the high symptom burden classes between the 'COVID-19 in last 12 weeks' and 'no COVID-19' groups we identified symptoms characteristic of acute COVID-19, including loss of taste and smell, fatigue, cough, shortness of breath and muscle pains or aches. Comparing the high symptom burden classes between the 'COVID-19 > 12 weeks ago' and 'no COVID-19' groups we identified symptoms characteristic of long COVID, including fatigue, shortness of breath, muscle pain or aches, difficulty concentrating and chest tightness. The identified symptom patterns among individuals with COVID-19 > 12 weeks ago were strongly associated with self-reported length of time unable to function as normal due to COVID-19 symptoms, suggesting that the symptom pattern identified corresponds to long COVID. Building the evidence base regarding typical long COVID symptoms will improve diagnosis of this condition and the ability to elicit underlying biological mechanisms, leading to better patient access to treatment and services. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has disrupted lives and livelihoods, and people already experiencing mental ill health may have been especially vulnerable.Aims: Quantify mental health inequalities in disruptions to healthcare, economic activity and housing.Method: We examined data from 59 482 participants in 12 UK longitudinal studies with data collected before and during the COVID-19 pandemic. Within each study, we estimated the association between psychological distress assessed pre-pandemic and disruptions since the start of the pandemic to healthcare (medication access, procedures or appointments), economic activity (employment, income or working hours) and housing (change of address or household composition). Estimates were pooled across studies.Results: Across the analysed data-sets, 28% to 77% of participants experienced at least one disruption, with 2.3-33.2% experiencing disruptions in two or more domains. We found 1 s.d. higher pre-pandemic psychological distress was associated with (a) increased odds of any healthcare disruptions (odds ratio (OR) 1.30, 95% CI 1.20-1.40), with fully adjusted odds ratios ranging from 1.24 (95% CI 1.09-1.41) for disruption to procedures to 1.33 (95% CI 1.20-1.49) for disruptions to prescriptions or medication access; (b) loss of employment (odds ratio 1.13, 95% CI 1.06-1.21) and income (OR 1.12, 95% CI 1.06 -1.19), and reductions in working hours/furlough (odds ratio 1.05, 95% CI 1.00-1.09) and (c) increased likelihood of experiencing a disruption in at least two domains (OR 1.25, 95% CI 1.18-1.32) or in one domain (OR 1.11, 95% CI 1.07-1.16), relative to no disruption. There were no associations with housing disruptions (OR 1.00, 95% CI 0.97-1.03).Conclusions: People experiencing psychological distress pre-pandemic were more likely to experience healthcare and economic disruptions, and clusters of disruptions across multiple domains during the pandemic. Failing to address these disruptions risks further widening mental health inequalities. [ABSTRACT FROM AUTHOR]

This study investigated the role of intelligence and its development across childhood in decision‐making in adolescence (age 11 years). The sample was 12,514 children from the UK's Millennium Cohort Study, followed at ages 3, 5, 7, and 11 years. Decision‐making (risk‐taking, quality of decision‐making, risk adjustment, deliberation time, and delay aversion) was measured with the Cambridge Gambling Task. Even after adjustment for confounding, intelligence was positively associated with risk adjustment and quality of decision‐making in both boys and girls. Furthermore, in girls risk adjustment was related positively to IQ gains. Our findings suggest that there are important, substantively, associations between intelligence and adapting behaviour to risk at the cusp of adolescence, the period when the response to risk can shape life trajectories. Statement of ContributionWhat is already known on this subjectIn children, intelligence and decision‐making, measured with gambling tasks, are inconsistently linked.This could be due to gambling tasks not separating risk‐taking from contingency‐learning.What the present study addsThis study measured 11‐year‐olds' decision‐making using a gambling task in which probabilities of different outcomes are presented explicitly.IQ was positively associated with risk adjustment and quality of decision‐making.Also significant were IQ gains (for risk adjustment, only in girls).There are links between intelligence and adapting behaviour to statistical risk in children. [ABSTRACT FROM AUTHOR]

Maternal heavy alcohol use during pregnancy is harmful to offspring's health and adjustment. However, findings from studies on lower levels of prenatal drinking are mixed; a few even predict positive cognitive and psychosocial outcomes. Given that alcohol is a neurotoxin and teratogen, scholars question developmental benefits and point to residual confounding as a potential explanation, particularly as light drinkers are positively selected with respect to health and socioeconomic status. Using prospective, intergenerational data from the nationally-representative Millennium Cohort Study (MCS) in the United Kingdom, we studied associations between mother's drinking during pregnancy and children's cognitive and psychosocial outcomes at ages 3, 5, 7, 11, and 14 years (n = 10,454). We included early life confounders (e.g., maternal education, health, smoking) and mother's cognitive ability, and assessed robustness of relationships across outcomes and alternate drinking classifications. Results of a series of multivariable regression models found no association between light drinking and cognitive and psychosocial outcomes up to and including the age of 14, after controlling for key confounders. Light drinking during pregnancy was linked to higher socioeconomic advantages (e.g., mothers' higher education, professional/managerial occupation, home ownership, cognitive scores), which together accounted for positive associations between light drinking and children's outcomes. Mother's cognitive ability was an especially important confounder. [ABSTRACT FROM AUTHOR]